Plot daily data on a 1-year calendar using Python and Matplotlib

This project is an adaptation of code posted by @SO_tourist on StackOverflow, here:
https://stackoverflow.com/a/61277350

It has not been developed into a full-fledged library at this stage. I simply collected it into a form that I find useful and am saving it here for posterity. As such, the library is half-baked and you should expect to have to hack on it a little to make it work for you.

• Python 3.6+
• Pandas
• Numpy
• Matplotlib

The library supports heatmap mode as well as annotated days for defined values. It will create a file with the given filename in any format supported by Matplotlib. The result will be fitted to a 8.5" x 11" page. The page can be optionally oriented either landscape or portrait. The entire plot may be annotated with defined colors using the highlight map, or it may be entirely heatmap, or a mixture of both. The output can contain a legend and/or a color bar.

The module provides one function for plotting the calendar:

create_year_calendar(df, year, title=None, filename=None, cmap='cool', hlmap={}, showcb=False, portrait=False)

• df (required)
  the Pandas DataFrame column with the data to plot. It must be indexed by a date timestamp. The values must be numbers. Dates with no data will be given a value of 0
• year (required)
  the calendar year to plot
• title
  the title of the plot. If None, set to "year"
• filename
  the filename to save. If None, set to "title.png"
• cmap
  the matplotlib colormap to use
• hlmap
  the highlight map, which is a dictionary of annotation values. The dict must map a data value key to a tuple of ('color', 'Name') where 'color' is a matplotlib color and 'Name' is a string that will be used on the legend. Use None as the name to exclude a color from the legend
• showcb
  a flag to create a color bar. True to draw a color bar legend
• portrait
  a flag to set page orientation. True for portrait, False for landscape

If you have the following data in CSV format:

A calendar plot is generated as follows:

import pandas as pd

from calendarplot import create_year_calendar

# load the CSV into a DataFrame
df = pd.read_csv('data.csv')
# convert the date strings to timestamps
df['Date'] = pd.to_datetime(df.Date)
# set the index to the Date column
df.set_index('Date', inplace=True)

# create the highlight map for all possible values, as we intend to cover the
# entire calendar.  Days with no data will get a value of 0 and by using None
# as the description, it won't show up in the legend
hlmap = {0: ('gainsboro', None),
         1: ('lightblue', 'Near Miss'),
         2: ('tomato', 'Hit')}

# create the calendar using the Value column
create_year_calendar(df['Value'], 2022, '2022 Safety Report', 'example.png', hlmap=hlmap)

The following is an example of a heatmap calendar plot:

import random
import datetime
import pandas as pd

from calendarplot import create_year_calendar

# create random data for every day of the year
datelist = []
valuelist = []
d = datetime.date(2022, 1, 1)
while d.year == 2022:
    # Gaussian distribution for a nicer appearance
    v = random.gauss(50, 20)
    # date indexes must be Pandas timestamps
    datelist.append(pd.Timestamp(d))
    valuelist.append(v)
    d += datetime.timedelta(days=1)

# create the DataFrame and set the index to the Date column
df = pd.DataFrame(data={'Date': datelist, 'Value': valuelist})
df.set_index('Date', inplace=True)

# create the calendar using the Value column
create_year_calendar(df['Value'], 2022, '2022 Heatmap', 'example2.png', cmap='Greens', showcb=True)